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22,922 results for “Collections as data”
Biomedical prototype for human movement data collection and basic collection procedure demonstrations
<p>Video explaining the usage of the 1st prototype of the device produced as well as basic collection procedure example.</p> <p>The video was originally published on <a href="https://www.youtube.com/watch?v=tWhNt0iaYUY">https://www.youtube.com/watch?v=tWhNt0iaYUY</a></p>
Odontometric Data from of all Tooth Types from Skeletal Collections in South Africa
<p>Biological profiles are used to assist in the identification of an unknown person. Sex estimation is important in this process as other aspects of the biological profile such as age-at-death, population affinity and stature depend on accurate sex estimates. For this research, we estimated sex using the dentition of three socially identified South African groups, namely black, white and coloured South Africans. A total of 906 crania from dissection room cadavers from three medical schools, including the Pretoria Bone Collection (University of Pretoria), the Raymond A Dart Collection (University of Witwatersrand) and the Kristen Collection (Stellenbosch University) were used. Four measurements were taken from the left and right sides of incisors, canines, premolars and molars. Measurements were standard from Hillson 2005 and include four permanent tooth crown dimensions: maximum mesiodistal, maximum buccolingual and molar diagonal diameters (mesiobuccal - distolingual and mesiolingual - distobuccal).</p>
Data and code for: Collective motion diminishes, but variation between groups emerges, through time in fish shoals
<p>Despite extensive interest in the dynamic interactions between individuals that drive collective motion in animal groups, the dynamics of collective motion over longer time frames are understudied. Using three-spined sticklebacks, <i>Gasterosteus aculeatus,</i> randomly assigned to twelve shoals of eight fish, we tested how six key traits of collective motion changed over shorter (within trials) and longer (between days) timescales under controlled laboratory conditions. Over both timescales, groups became less social with reduced cohesion, polarisation, group speed and information transfer. There was consistent inter-group variation (i.e. collective personality variation) for all collective motion parameters, but groups also differed in how their collective motion changed over days in their cohesion, polarisation, group speed and information transfer. This magnified differences between groups, suggesting that over time the 'typical' collective motion cannot be easily characterised. Future studies are needed to understand whether such between-group differences in changes over time are adaptive and represent improvements in group performance or are suboptimal but represent a compromise between individuals in their preferences for the characteristics of collective behaviour.</p>
The bear cuscus presence data collection
<p>The table contains information about the number of points of the bear cuscus presence data collection in Bantimurung Bulusaraung National Park (BBNP) and Hasanuddin University Educational Forest (HUEF), South Sulawesi. The data collection consists of direct encounters, feed remains, claw marks, information from the local guides, calls, and BBNP's inventory data.</p>
VPM 8-17 Burst Collection Data
<p>VPM Burst data for Reid et. al 2022 in .xml and .mat format.</p> <p>This VPM burst data collection on 08/17/2020 has been approved for public release by AFRL specifically for this publication.</p>
Risk of bias in observational studies using routinely collected data of comparative effectiveness research: a meta-research study
<p>We performed a meta-research study by searching PubMed for comparative effectiveness observational studies evaluating therapeutic interventions using routinely collected data published in high impact factor journals from 01/06/2018 to 30/06/2020. We assessed the reporting of study design (i.e., eligibility, treatment assignment, and the start of follow-up). Risk of selection bias and immortal time bias was determined by assessing if the time of eligibility, treatment assignment and the start of follow-up were synchronised to mimic the randomisation following the target trial emulation framework.</p>
Collecting data on Hungarian traditional/local pulse varieties, on legume production, consumption and trade of food-purpose pulses in Hungary
<p>Summary data on traditional and local Hungarian pulse varieties will be provided. This will include a systematic summary of all legume species and varieties used for food and feed that are stored in the seed bank data of the National Plant Diversity Centre, Hungary.</p> <p>Statistical data mined from the database of the Hungarian Central Statistical Office (CSO) on the production of the most significant food and feed legumes in Hungary, the household consumption of the some food-used pulses, as well as the food industry processing and the national trade of pulses.</p> <p>Mining and summarizing existing data from different resources will be performed during 2017 and will be provided by February 2018. Statistical data on production, consumption and traded will be supplemented during the project with the updates of CSO databases. Methodologies used will be desk research and primer analysis.</p>
APPENDIX 2 in New data on the distribution of the two mole species Talpa aquitania Nicolas, Matinez-Vargas & Hugot, 2017 and T. europaea Linnaeus, 1758 in France based on museum and newly collected specimens
APPENDIX 2. — Continuation.
Chemical imaging data collected on wood board sections after impregnation-treatment with phenol formaldehyde resin
<p>This dataset contains UV microspectrophotometry (UMSP) and near infrared (NIR) imaging data from the following publication: Altgen M., Awais M. Altgen D., Klüppel A., Koch G., Mäkelä M., Olbrich A., Rautkari L. (2022) Chemical imaging to reveal the resin distribution in impregnation-treated wood at different spatial scales. Materials & Design, DOI: <a href="https://doi.org/10.1016/j.matdes.2022.111481">https://doi.org/10.1016/j.matdes.2022.111481</a>.</p> <p>The data was obtained from beech wood board sections (75x15x25 mm<sup>3</sup>) that were impregnation-treated with a low molecular weight phenol formaldehyde resin. Experimental details can be found in the publication.</p> <p>The file “NIR sample IDs with weight and dimensional changes.csv” contains the sample IDs and the weight percent gains caused by the resin treatment of each sample in the dataset. To generate the NIR image files, regions of interest of 881 x 384 pixels (subsets a,b,c,d) or 2401 x 375 pixels were selected from the raw image files to produce an image that contains the sample surrounded by background. The spectral data was corrected using the calibration reflectance target values and then converted to absorbance. Each NIR image is stored in a separate MATLAB file (.mat) with the sample ID as the file name.</p> <p>The file "UMSP sample IDs.csv" contains the sample IDs of the UMSP images. The folder "UMSP image profiles.zip" contains the corresponding UMSP image profiles, which are stored as excel files (.xlsx) with the sample IDs as file names. The files contain the absorbance at 278 nm per pixel with a pixel resolution of 0.25 x 0.25 µm<sup>2</sup>.</p>
Chemical imaging data collected on small wood cubes after impregnation-treatment with phenol formaldehyde resin
<p>This dataset contains UV microspectrophotometry (UMSP) and near infrared (NIR) imaging data from the following publication: Altgen M., Awais M. Altgen D., Klüppel A., Koch G., Mäkelä M., Olbrich A., Rautkari L. (2022) Chemical imaging to reveal the resin distribution in impregnation-treated wood at different spatial scales. Materials & Design, DOI: <a href="https://doi.org/10.1016/j.matdes.2022.111481">https://doi.org/10.1016/j.matdes.2022.111481</a>.</p> <p>The data was measured on small beech wood cubes (15x15x15 mm<sup>3</sup>) that were impregnation-treated with a low molecular weight phenol formaldehyde resin. Experimental details can be found in the publication.</p> <p>The file “NIR sample IDs with weight and dimensional changes.csv” contains the sample IDs as well as the weight percent gains and dimensional changes caused by the resin treatment of each sample in the dataset. To generate the NIR image files, a region of interest of 881 x 384 pixels was selected from the raw image files to produce an image that contains the sample surrounded by background. The spectral data was corrected using the calibration reflectance target values and then converted to absorbance. Each NIR image is stored in a separate MATLAB file (.mat) with the sample ID as the file name.</p> <p>The file "UMSP sample IDs.csv" contains the sample IDs of the UMSP images. The folder "UMSP image profiles.zip" contains the corresponding UMSP image profiles, which are stored as excel files (.xlsx) with the sample IDs as file names. The files contain the absorbance at 278 nm per pixel with a pixel resolution of 0.25 x 0.25 µm<sup>2</sup>.</p>
Surface and subsurfaca data collected during artificial rainfall experimetns on tilled soil with wheel tracks
<p>This dataset contains data measured during the artificial rainfall experiment conducted within the project LTC18030 - The effects of land use changes on soil erosion, sediment transport, water quality and runoff conditions in 2018 and 2019 at experimental site Řisuty, Czech Republic.</p> <p>This dataset contains raw data (xlsx, csv) and images of more qualitative data such as electrical resistivity tomography profiles.</p> <p>For further information about the experiments and analysis please check: Jeřábek, J., Zumr, D., Laburda, T., Krása, J., Dostál, T., 2022. Soil surface connectivity of tilled soil with wheel tracks and its development under simulated rainfall. J. Hydrol. 613. https://doi.org/10.1016/j.jhydrol.2022.128322</p> <p><strong>The dataset consists of following files: </strong></p> <ul> <li>experimental_plots_overview.pdf: overview of the setup and map of the experimental site</li> <li>electrical_resistivity_tomography.pdf: overview of the ERT measurement is provided in this file</li> <li>penetrometry.pdf: penetrometry was done in and in the vicinity of the experimental plot</li> <li>basic_variables_of_experiments.xlsx: basic information about each of the experiments</li> <li>measuted_soil_hydraulic_properties.xlsx: summarised the measured soil hydraulic propertie for all used method and for each plot</li> <li>optimized-parameters-all.xlsx: optimal parameters for all optimized scenarios</li> <li>optimized-parameters-stats.xlsx: statistics of optimal parameters for each soil layer and plot</li> <li>vol1-soil-water-retention-data.xlsx: soil water retention data from the sand tank and pressure chamber measurement of the vol1 experiment</li> <li>vol2-soil-water-retention-data.xlsx: soil water retention data from the sand tank and pressure chamber measurement of the vol2 experiment</li> <li>soil_loss.csv: soil loss time series</li> <li>surface_runoff.csv: surface runoff time series</li> <li>soil_water_pressure.csv: soil water pressure time series</li> <li>soil_water_pressure_positions.csv: position of tensiometers on each plot</li> <li>volumetric_water_content.csv: volumetric water content time series</li> <li>volumetric_water_content_positions.csv: position of vwc probe on each plot</li> <li>start_stop_rainfall_info.csv: information about the time span of each experiment</li> </ul>
Northern Nevada wildlife and topography: Camera trapping data set for 14 mammal species collected from 100 sampling sites in northwestern Nevada
<p>Camera traps are one of the most common field techniques for surverying terrestrial mammal communities and thus, much work has gone into understanding how different factors influence species detection at camera trap locations. However, the effect of fine-scale topography, such as terrain slope and position, on wildlife detection has not been explicitly quantified despite strong effects of topography on animal movement in mountainous regions. This data set contains weekly detection non-detection data for 14 mammal species from 100 camera traps sites monitored for 28 months (June 2018 - September 2020) in northwestern Nevada, U.S.A. This sampling extent was split into 3 month sampling seasons, exclusive of winter (Dec, Jan, Feb) and spring 2020, when data were sparse. In addition to species detection data, that dataset includes topographic variables at cameras sites: 1) terrain slope, calculated in R package raster from a 10m digital elevation model and 2) Topographic position index averaged across three buffer sizes around points 270m, 810m, and 2430m. The land cover variables proportion mixed conifer and proportion pinyon-juniper woodland within a 5000m buffer of sites are also included. Both are derived from the USDA/US DOI Landfire 2016 dataset. The luring variable indicates whether attractant was applied at a site during a given week, the effect of which was assumed to last for a month after the last application. </p>
Dataset supporting publication: "Data collected by coupling fix and wearable sensors for addressing urban microclimate variability in an historical Italian city"
<p>Dataset supporting publication: “Data collected by coupling fix and wearable sensors for addressing urban microclimate variability in an historical Italian city” (publication available for download: <a href="https://zenodo.org/record/3901556">GEOFIT Zenodo</a>)</p> <p>Datasets resulting from monitoring activities of Sant'Apollinare systems and climatic parameters inside and outside the building (post-intervention monitoring).</p> <p>The article presents the data collected through an extensive research work conducted in a historic hilly town in central Italy during the period 2016-2017. Data concern two different datasets: long-term hygrothermal histories collected in two specific positions of the town object of the research, and three environmental transects collected following on foot the same designed path at three different time of the same day, i.e. during a heat wave event in summer. The short-term monitoring campaign is carried out by means of an innovative wearable weather station specifically developed by the authors and settled upon a bike helmet. Data provided within the short-term monitoring campaign are analysed by computing the apparent temperature, a direct indicator of human thermal comfort in the outdoors. All provided environmental data are geo-referenced. These data are used in order to examine the intra-urban microclimate variability. Outcomes from both long- and short-term monitoring campaigns allow to confirm the existing correlation between the urban forms and functionalities and the corresponding local microclimate conditions, also generated by anthropogenic actions. In detail, higher fractions of built surfaces are associated to generally higher temperatures as emerges by comparing the two long-term air temperature data series, i.e. temperature collected at point 1 is higher than temperature collated at point 2 for the 75% of the monitored period with an average of þ2.8 [1]C. Furthermore, gathered environmental transects demonstrate the high variability of the main environmental parameters below the Urban Canopy. Diversification of the urban thermal behaviour leads to a computed apparent temperature range in between 33.2 [1]C and 46.7 [1]C at 2 p.m. along the monitoring path. Reuse of these data may be helpful for further investigating interesting correlations among urban configuration, anthropogenic actions and microclimate variables affecting outdoor comfort. Additionally, the proposed dataset may be compared to other similar datasets collected in other urban contexts around the world. Finally, it can be compared to other monitoring methodologies such as weather stations and satellite measurements available in the location at the same time.</p>
Biogeochemical data of sinking particulate matter collected by sediment traps at E2M3A mooring (2013-2020) in the Southern Adriatic Sea
<p>The dataset presented (NetCDF format), includes sediment trap derived fluxes (total mass, POC, CaCO<sub>3</sub>, bSiO<sub>2</sub>) at ~1200 m depth from the E2M3A deep-sea mooring in the center of the Southern Adriatic Sea in the period from December 2013 to September 2020. The E2M3A observatory is positioned in the centre of the cyclonic gyre where deep convection process takes place, involving both the atmosphere and the ocean dynamics and forming new dense and oxygenated waters, thus triggering the biological pump. The E2M3A mooring is included in the southern Adriatic regional facilities of EMSO-ERIC consortium managed from OGS Trieste and CNR-ISP. Sediment traps, positioned at two levels (below the photic layer at -120m and near the bottom at -1050m), allow the understanding of the processes responsible for the high-frequency and interannual variability of new production and of phytoplankton biomass. Total mass fluxes (TMF) measured at the shallower trap were generally lower that those measured at the bottom trap, ranging from 16 to 706 mg m<sup>-2</sup> d<sup>-1</sup>, with a time-weighted average of 133 mg m<sup>-2</sup> d<sup>-1</sup>, whereas at the bottom trap TMF varied from 33 to 885 mg m<sup>-2</sup> d<sup>-1</sup>, with a time-weighted average of 190 mg m<sup>-2</sup> d<sup>-1</sup>. The organic carbon flux, followed the same seasonal trend, with higher values below the photic zone, varying from 1.7 to 31.9 mg m<sup>-2</sup> d<sup>-1</sup>, with a mean of 5.8 mg m<sup>-2</sup> d<sup>-1</sup> at the shallow trap.</p>
A Twitter Streaming Data Set collected before and after the Onset of the War between Russia and Ukraine in 2022
<p>Social media can be mirrors of human interaction, society, and world events. Their reach enables the global dissemination of information in the shortest possible time and thus the individual participation of people all over the world in global events in almost real-time. However, equally efficient, these platforms can be misused in the context of information warfare in order to manipulate human perception and opinion formation. The outbreak of war between Russia and Ukraine on February 24, 2022, demonstrated this in a striking manner. </p> <p>Here we publish a dataset of raw tweets collected by using the Twitter Streaming API in the context of the onset of the war which Russia started on Ukraine on February 24, 2022. A distinctive feature of the dataset is that it covers the period from one week before to one week after Russia's invasion of Ukraine. We publish the IDs of all tweets we streamed during that time, the time we rehydrated them using Twitter's API as well as the result of the rehydration. If you use this dataset, please cite our related Paper: </p> <blockquote> <p>Pohl, Janina Susanne and Seiler, Moritz Vinzent and Assenmacher, Dennis and Grimme, Christian, A Twitter Streaming Dataset collected before and after the Onset of the War between Russia and Ukraine in 2022 (March 25, 2022). Available at SSRN: <a href="https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4066543">https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4066543</a></p> </blockquote>
Data for: "Dynamics of collective motion across time and species"
<p>This repository contains the data accompanying the paper:</p> <p><strong>Papadopoulou M., Fürtbauer I., O’Bryan L., Garnier S., Georgopoulou D., Bracken A., Christensen C., and King A.J. (2022) "Dynamics of collective motion across time and species". Phil. Trans. R. Soc. B 20220068 <a href="https://doi.org/10.1098/rstb.2022.0068">https://doi.org/10.1098/rstb.2022.0068</a></strong></p> <p>This work is supported by an Office for Naval Research (ONR) Global Grant (N629092112030) awarded to AJK.</p>
Raw data for the Github repository "Collection of scripts to download & process hydropower generation data in Argentina, Bolivia, Brazil, Uruguay"
<p>This is the raw data downloaded from the websites of the following system operators:</p> <p> - CNDC, Comité Nacional de Despacho de Carga (Bolivia): https://www.cndc.bo/home/index.php<br> - ONS, Operador Nacional do Sistema Elétrico (Brazil): https://www.ons.org.br/<br> - UTE, Usinas y Trasmisiones Eléctricas (Uruguay): https://www.ute.com.uy/<br> - CAMMESA, Compañía Administradora del Mercado Mayorista Eléctrico Sociedad Anónima (Argentina): https://cammesaweb.cammesa.com</p> <p>Hydropower generation data is extracted using the R scripts available here: https://github.com/matteodefelice/hydro-sam</p>
Collection and ddRadSeq sequencing data for Sitophilus zeamais from Oaxaca and Chiapas, Mexico
<p>The maize weevil, <em>Sitophilus zeamais</em>, is a ubiquitous pest of maize and other cereal crops worldwide and remains a threat to food security in subsistence communities. Few population genetic studies have been conducted on the maize weevil, but those that exist have shown that there is very little genetic differentiation between geographically dispersed populations and that it is likely the species has experienced a recent range expansion within the last few hundred years. While the previous studies found little genetic structure, they relied primarily on mitochondrial and nuclear microsatellite markers for their analyses. It is possible that more fine-scaled population genetic structure exists due to local adaptation, the biological limits of natural species dispersal, and the isolated nature of subsistence farming communities. In contrast to previous studies, here, we utilized genome-wide single nucleotide polymorphism data to evaluate the genetic population structure of the maize weevil from the southern and coastal Mexican states of Oaxaca and Chiapas. We employed strict SNP filtering to manage large next generation sequencing lane effects and this study is the first to find fine-scale genetic population structure in the maize weevil. Here, we show that although there continues to be gene flow between populations of maize weevil, that fine-scale genetic structure exists. It is possible that this structure is shaped by local adaptation of the insects, the movement and trade of maize by humans in the region, geographic barriers to gene flow, or a combination of these factors.</p>
Data collected in Malaysia
<p>Data collected in Malaysia over the duration of the project. This includes quantitative and qualitative data from surveys, interviews and focus groups collected online and face to face.</p>
Data Collection and Manipulation Template for MAED (Model for Analysis of Energy Demand)
<p>A Data Collection and Manipulation Template for MAED (Model for Analysis of Energy Demand). </p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.